A New Tool for Building Energy Optimization: First Round of Successful Dynamic Model Simulations

Abstract

Several tools and pieces of software support building energy modelling for optimization, certification and comparisons of different scenarios and usages. Nevertheless, the consistent rise in accessible computational power and the expansion of ICT are pushing the development of new software functionalities and tools able to support cross-disciplinary work on smart building optimization. This paper introduces a new platform (under development) that combines the EnergyPlus dynamic simulation tool with extra-functionalities and pre-defined usage scenarios based on automatic actions to manage massive simulations and correlation analyses. The tool’s utility was tested in three experiments, with goals that we consider to be fundamental requirements: comparing simple retrofit actions to reduce net energy needs; analyzing the free-running potential of a demo building and the impacts of different low-energy technologies in terms of increasing thermal comfort (shading and ventilative cooling); and comparing measured sensor data indicators with simulated ones under real weather conditions for model verification. The results demonstrate the ability of the tool to automatically generate hundreds of EnergyPlus input building models by acting on building geometry; we focused on the most common uses for parametric dynamic simulations. Additionally, the way in which the tool combines the automatic modification of the building’s design and the parallel launching of multiple simulations allows the labor to be reduced. The user can execute complex tasks without spending any time working with model editing software and aggregating the results from multiple simulations.

Impact of different thermal zone data simplification for model calibration on monitored-simulated performance gaps

“…entrance-exit hours, number of children). Both standard and adapted conditions are simulated, and results compared with the same indicators computed from monitored data, exploiting an automatic performance gap analysis scenario developed inside the PREDYCE tool [8]. As main indicators, the operative temperature and the Adaptive Comfort Model (ACM) are considered: ACM POR (Percentage Outside the Range) is defined as the percentage of hours in thermal discomfort, adopting Cat.…”

“…Moreover, different thermal zones' aggregations, going from room details to multispace aggregations according to the orientations of windows and finally to floor averages, are also tested. The calibration procedure is run using semi-automatic parametrisations by changing EnergyPlus model inputs exploiting the new PREDYCE python library developed by the authors [8]. Results of the different tests analyse the calibration process complexity considering the needed elaboration time and data and the statistical feasibility of the calibrated model in representing the building behaviour at different granularity, both spatial (average building; single zones) and temporal.…”

Method combining expert and analytical approaches towards economical energy renovation roadmaps and improved indoor comfort

“…The analytical approach uses a dynamic simulation platform, described in [13], that allows for massive sensitivity analysis on main design parameters. Analytical platform is linked to environmental variables like indoor comfort models, temperature levels, and energy.…”

E-DYCE - Dynamic approach to the dynamic energy certification of buildings

“…CO2 level is above 900 ppm). • Free-running operation KPIs [9] can address issues in the certification of low-tech buildings but also can be used to support passive strategies application in all types of buildings (also mechanically operated buildings).…”

“…. PREDYCE PREDYCE (Python semi-Realtime Energy DYnamics and Climate Evaluation) is a Python library that can act as a dynamic simulation platform, adopting EnergyPlus as simulation engine[9]. Its architecture is based on EU H2020 project E-DYCE (893945), while extra functionalities and scenarios of use are based on project PRELUDE (958345).…”